Self-generated complexity and human-machine interaction

Schlick, Christopher; Winkelholz, Carsten; Motz, Florian; Luczak, Holger

doi:10.1109/tsmca.2005.859096

Cited by 16 publications

(6 citation statements)

References 23 publications

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“…As was already pointed out when formulating the hypotheses, the previous study focused on bichromatic radar displays instead of ECDIS and the users were not exposed to motion forces (see Schlick et al 2006). In the previous study, it was discovered that there is a significant workloadcomplexity trade-off; the higher the mental workload due to time pressure, the lower the complexity generated by visual perception, cognition and motor response (under constant performance).…”

Section: Resultsmentioning

confidence: 99%

“…The predicted OIE for a certain prediction context c is simply the event that holds the maximum of the probability mass, which is distributed over the vector components of p c . More details on context tree construction and complexity estimation are given in Schlick et al (2006). The full tree construction algorithm can be found in Bu¨hlmann and Wyner (1999).…”

Section: Complexity Estimationmentioning

confidence: 99%

“…In a previous laboratory study of Schlick et al (2006), it was shown that the complexity measure is a valid indicator of mental workload due to time pressure; the larger the mental workload, the lower the complexity of the corresponding visual search processes. The previous study involved 30 German master mariners, who had to search for multiple targets, but bichromatic radar displays were used instead of ECDIS and the users were not exposed to motion forces.…”

Section: Hypothesesmentioning

confidence: 99%

“…However, there is a common theoretical ground and the different meanings simply reflect the fact that complexity is an inherently multi-faceted phenomenon. In previous papers of Schlick et al (2004Schlick et al ( , 2006, the introduced theory was successfully used to assess emergent complexity in general human-machine systems. The following calculation example and validation study will show that EMC is also a promising measure for ergonomic design and evaluation of human-computer interaction.…”

mentioning

confidence: 99%

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Complexity assessment of human–computer interaction

Schlick

Winkelholz²,

Motz³

et al. 2010

Theoretical Issues in Ergonomics Science

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A quantitative complexity theory of human-computer interaction is presented and validated by means of laboratory experiments. Based on the seminal work of Grassberger in theoretical physics, a complexity measure is introduced. The measure is termed the Effective Measure Complexity and has three main advantages. First, it relies solely on information-theoretic quantities, which are intimately connected with the concept of complexity and not randomness. Second, it is model independent and can be estimated efficiently from data. Third, the estimates can be derived from behavioural patterns in terms of observable interaction events alone. Subjective ratings or psychophysiological measurements can be included but are not mandatory. In order to explain the theory, a simple and easy to generalise example in mobile human-computer interaction is presented. Furthermore, the external validity of the complexity measure is studied in laboratory experiments. The experimental task was to search for multiple targets on an electronic chart display and information system (ECDIS). ECDIS is an integral component of modern ship bridge concepts and therefore the experiments were carried out in a marine simulator. Thirty users participated. The platform motion (with or without motion) and the workplace illumination (800 lux or 30 lux) were varied systematically and the complexity effects were studied. The results show that the complexity of the visual search processes is significantly lower when the simulator is put in sea state characteristics and the users are facing straining motion forces. In addition, interaction complexity is significantly lowered when illuminance is reduced from the daylight level of 800 lux to the twilight level of 30 lux. Therefore, the complexity measure seems to be a valid for the quantitative assessment of human-computer interaction.

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Section: Resultsmentioning

confidence: 99%

Section: Complexity Estimationmentioning

confidence: 99%

Section: Hypothesesmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Complexity assessment of human–computer interaction

Schlick

Winkelholz²,

Motz³

et al. 2010

Theoretical Issues in Ergonomics Science

Self Cite

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show abstract

“…In the future, predictive performance models such as Fitts' law can also help software designers to build anticipatory user interfaces that provide automatic adaptation of the layout and size of interface objects according to task demands as well as a user's behaviour and preferences (Schlick et al 2006). By doing so, we will also be able to evaluate the impact of our findings on real project-planning and scheduling problems in industrial companies.…”

Section: Discussionmentioning

confidence: 94%